International Symposium on Performance Science
ISBN 978-94-90306-02-1
© The Author 2011, Published by the AEC
All rights reserved
Verbal expression of piano timbre:
Multidimensional semantic space of adjectival
descriptors
Michel Bernays and Caroline Traube
Faculty of Music, University of Montreal, Canada
High-level pianists refer to and can identify nuances in timbre by way of
a wide and rich vocabulary, whose abstract, imaged, and metaphoric
terms acutely designate a variety of sounds. This timbre-describing lexicon is hereby studied quantitatively. The semantic proximity between
pairs taken among 14 common piano timbre descriptors was evaluated in
questionnaires distributed to 17 pianists. Ratings were analyzed with
multidimensional scaling algorithms, yielding a four-dimensional space
representing the semantic proximity between descriptors. Using cluster
analyses, five main subsets were identified, within which the most familiar terms were selected. We thus obtained five descriptors which optimally describe the whole semantic space for the group of pianists taking
part in this study: bright, dry, dark, round, and velvety.
Keywords: piano; timbre; verbal description; semantic space; multidimensional scaling
Timbre is an essential feature of musical expressivity in virtuosic pianistic
performance. Timbre indeed intervenes, not solely as a characteristic of the
instrument, but also as performers can modulate and shape sounds in order
to express their musical intentions. Such ability to modulate timbre in very
subtle ways usually stems from the piano learning process within which, at
the higher level, timbre concepts, emotions to instill, and the adequate sound
are conjointly demonstrated to the student through masterly performances.
Those come along with an extensive vocabulary, whose imagery in terms such
as clear, warm, metallic, or shimmering, aims at evoking the sonic nuances.
While many timbre studies (e.g. Grey 1977, McAdams et al. 1995) have
dealt with building perceptual timbre spaces, they only compared timbre perception between different instruments without delving into one single in-
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strument’s timbral subspace. Others have focused on timbre verbalization
and managed to define axes or spaces of timbre description (e.g. Von
Bismarck 1974, Disley et al. 2006). However, attempts to weld semantic and
perceptual spaces (Faure 2000) mostly proved unsuccessful. In the specific
case of the piano, Ortmann (1929) linked common piano timbre verbal descriptors with characteristics of touch but only in relation with single notes.
More recently, the study of free verbalization (Cheminée et al. 2005) revealed
the specificity of the pianists’ sound-describing lexicon, built upon an affective and axiological vocabulary following two axes: percussion and resonance.
Bellemare and Traube (2005) studied piano timbre verbalization through
interviews of 16 highly trained pianists—thus was gathered a comprehensive
collection of close to one hundred terms, detailed with descriptions, synonymic relationships, and frequency of occurrence.
On the basis of this verbal data collection, our study explores further the
piano timbre-describing vocabulary and quantifies its semantic structure. To
this aim, pianists were asked to determine the semantic similarities between
descriptors. We thus aimed at building a spatial representation of semantic
relationships between piano timbre descriptors, while focusing in identifying
therein the most encompassing subset of descriptors that would suffice to
accurately describe the whole space.
METHOD
Participants
Seventeen pianists, most of them from the Faculty of Music at the University
of Montreal, plus others from elsewhere in Canada, France, and Finland, took
part in the study by filling in questionnaires, either on paper or electronically.
Materials
The questionnaires were conceived to probe the semantic similarities between
common piano timbre descriptors. The 20 most frequently cited descriptors
in Bellemare and Traube (2005) were first selected. Then, in light of the synonymic relationships between them, the corpus was downsized to the following 14 terms: brassy, bright, clear, dark, distant, dry, full-bodied, harsh,
metallic, muddled, round, shimmering, soft, and velvety.
Procedure
The participants were asked to rate their familiarity with each adjective, then
to rate the semantic proximity between each of the 91 pairs of adjectives from
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Figure 1. Mean evaluation of familiarity with piano timbre verbal descriptors.
the 14 terms set. All ratings were indicated on six-degree, zero-to-five Likerttype scales. The printout order was randomized for each questionnaire.
Questionnaires were filled in and sent back anonymously.
RESULTS
Familiarity with timbre descriptors
The evaluations of familiarity with the fourteen piano timbre descriptors,
gathered from the seventeen filled-in questionnaires, were averaged per descriptor. The resulting means are presented in Figure 1.
The large variability in familiarity assessment between participants—as
the error bars (±2 standard errors) in Figure 1 indicate—may impair any generalized conclusions, yet shall let us use those familiarity rankings for the
sheer purpose of highlighting one descriptor within a subset.
Dissimilarities and semantic space
Meanwhile, the assessments of semantic proximity were compiled as similarity matrices, then reversed and metrically re-scaled in dissimilarity matrices,
which were fed into a metric multidimensional scaling algorithm. The optimal
dimensionality was set at four, as the fourth dimension yields the last significant stress improvement (over 0.001) and is the last within which distances
are of significant range and seem meaningful and interpretable. The resulting
space is displayed in Figures 2 and 3. The associated stress value is 0.045.
The distances between descriptors in this 4D space show a linear correlation
(r-squared) of r²=0.931 with the original 14-dimension dissimilarities. Each
dimension accounts for respectively 49.3%, 27.7%, 13.4%, and 9.6% of the
MDS reconstruction (by way of the space’s eigenvalues ratios).
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Figure 2. Planar projections of the 4D MDS semantic space: dimensions 1 vs. 2 and
dimensions 3 vs. 4.
Figure 3. Display of the first three dimensions from the 4D MDS semantic space.
As for accounting for the dimensions’ semantic meanings, conjectures
may be made that the first dimension is associated to “sharpness” or “brightness”—acoustically, simply put, the relative amount of higher frequencies.
The second dimension may account for “warmth”—acoustically, the relative
amount of low-to-mid frequencies. The third and fourth dimensions are more
difficult to assess, although the third dimension may relate to some inherent
timbre “loudness,” and the fourth may seem akin to “presence.”
Cluster analysis
In addition to the multidimensional scaling of the dissimilarity data, hierarchical clustering was performed with different distance measures: weighted
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Figure 4. Dendrogram of the descriptors’ dissimilarities hierarchical clustering. (See full
color version at www.performancescience.org.)
and unweighted average (WPGMA and UPGMA, respectively), furthest distance, and inner squared distance (i.e. minimum variance). K-means partitioning algorithms were likewise ran. Results were essentially similar between
methods, with the only difference the strength of linkage between “brassy”
and “metallic” at the sixth-cluster level. The semantic clustering tree of descriptors, with UPGMA as distance measure, is presented in Figure 4.
DISCUSSION
To identify the clusters within the semantic structure of piano timbre descriptors, the MDS semantic space was first examined. Over the dimensions
1-vs.-2 plan—which accounts for 73.5% of the dispersion—five groups were
singled out within the descriptors’ set: [brassy, bright, clear, shimmering],
[full-bodied, round], [soft, velvety], [dry, harsh, metallic], [dark, distant,
muddled]. Those exactly match 5-branch subsets resulting from the cluster
analysis (see Figure 4). For each of those five clearly identified subgroups,
one single representative term was sought out with regard to the familiarity
ratings and also to the relations between timbre and dynamic levels (see
Bellemare and Traube 2005). Timbres too dynamically constrained or which
double as dynamics descriptors, especially when unfit for a mf dynamic (i.e.
soft and distant), were discarded. Also favored were the descriptors that best
helped describe the MDS dimensions 3-vs.-4 plan, whose subsetting outlook
is less salient. Finally, the five terms that best represent the whole semantic
space of piano timbre descriptors are: bright, dry, dark, round, and velvety.
The spatial representation of piano timbre descriptors may prove a useful
pedagogical tool for pianists, in facilitating access to understanding timbre as
a multidimensional concept. The selection of the most encompassing piano
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timbre descriptors will now be employed to study the gestural control of piano timbre. Miniature piano pieces were composed so as to fit each of the five
timbres, and the gestures applied by pianists to color their performances will
be analyzed, in the aim of obtaining a gestural mapping of piano timbre that
could prove relevant to piano pedagogy and software modelization.
Acknowledgments
We wish to thank the participants, as well as the piano teachers from the Faculty of
Music who helped and distributed the questionnaires among their students.
Address for correspondence
Michel Bernays, Faculty of Music, University of Montreal, 200 Avenue Vincent d’Indy,
Montreal, Quebec H2V 2T2, Canada; Email: [email protected]
References
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